IDEA25 Faculty Bios
Claire Baytas
Claire Baytas is a senior analyst on the Libraries, Scholarly Communication, and Museums team, working in the research enterprise program area. Her work at Ithaka S+R to date has focused on the effects of generative AI on teaching, learning, and research. Before joining Ithaka S+R, Claire completed a PhD in comparative literature at the University of Illinois.
Charlene Chou
Charlene Chou is the Head of the Knowledge Access Department at New York University Libraries, where she oversees cataloging and metadata services. She has contributed to national and international standards for metadata interoperability through active service on various committees, including the PCC (Program for Cooperative Cataloging) Policy Committee, the PCC Task Group on AI and Machine Learning for Cataloging and Metadata, the RDA Steering Committee, the BIBFRAME Interoperability Group, and the Joint RDA Board and RSC Working Group on Artificial Intelligence. She is committed to conducting pilot projects on emerging trends and technologies. Her research interests focus on metadata management, the discovery of multilingual resources, natural language processing (NLP) models for subject indexing and semantic search, digital scholarship, authority control, linked data, and inclusive metadata.
Andrew Cox
Andrew Cox is a Senior Lecturer at University of Sheffield. After graduating from Aberystwyth with an MSc in Library Studies, he spent a number of years working in development projects around the use of ICT in library contexts, funded by EC, JISC and others. He completed his PhD at Loughborough in 2006. Much of his research relates to the information professions and their response to contemporary trends such as artificial intelligence, datafication and managerialism. He is Programme Coordinator, MSc Information Management and Module Coordinator, Archives and Records Management. In the past he has been the School’s Director of Learning and Teaching, Postgraduate Research Director and Director of Research.
Satanu Ghosh
Satanu Ghosh is a Computer Science PhD student at the University of New Hampshire. With about nine years of research experience in Natural Language Processing and Information Science, he works with LLMs with Bayesian optimization to enhance material science discovery with transparency. Satanu has published in top-tier ACM and IEEE conferences on topics in information retrieval, digital libraries, and deep neural networks.
Souvick Gosh
Dr. Souvick 'Vic' Ghosh is a Tenure-Track Assistant Professor at the School of Information at San Jose State University. With a background in Human-Computer Interactions (HCI) and Artificial Intelligence (AI), Dr. Ghosh specializes in applications that solve complex problems in information systems. His work encompasses conversational search systems, ethical AI, and the protection of Personal Identifiable Information (PII) through AI automation. He is the Chair-Elect for ASIS&T SIG-Social Media, the Chair for the IDEA Institute on AI, and the Director of the Intelligent Conversational Agents and Neural Networks Lab at SJSU.
Jiangen He
Jiangen He is an assistant professor in the School of Information Sciences at the University of Tennessee, Knoxville. He holds a PhD in Information Science from Drexel University. His research includes science of science, AI in science, information visualization, and human-AI interaction.
Darra Hoffman
Dr. Darra Hofman received their Ph.D. in library, archival, and information science from The University of British Columbia in 2020. They completed her M.L.I.S. from the University of Kentucky and her J.D. and B.A. (honors) from Arizona State University. Their research examining the intersection of archives, technology, and law has been published in a number of journals, conference proceedings, and edited collections. In particular, they are interested in privacy, blockchain technologies, and health records.
Lingzi Hong
Lingzi Hong is an Assistant Professor in Data Science in the College of Information at the University of North Texas. Her research is situated within the field of computational social science, where she employs computational linguistics and information behavior modeling methods to explore ways to facilitate information processing and communication among users. She has research published in top-tier computer science conferences such as AAAI, NAACL, ICWSM, EMNLP, and journals such as International Journal of Human Computer Interaction, Library and Information Science Research, and EPJ Data Science. She is currently the Chair-elect of the ASIS&T SIG Social Media.
Jinyu Liu
Jinyu Liu is a PhD student in Information Science at the University of North Texas. Jinyu’s research interest includes the development of LLM applications for information organization.
Brady Lund
Brady Lund is an assistant professor of information science at the University of North Texas and co-director of the Culture, Humanities, and Inclusion Lab (CHILL). Brady’s work seeks to develop an understanding of critical ethical and societal issues related to the emergence of the fourth industrial revolution, particularly artificial intelligence, including within the library context. He has published over 100 articles in journals including the Journal of the Association for Information Science and Technology, Library and Information Science Research, College and Research Libraries, Journal of Academic Librarianship, and Information Technology and Libraries.
Natalie Meyers
Natalie Meyers is the first ARL/CNI researcher in residence. She focuses on the strategic implications of artificial intelligence (AI) for research libraries, furthering the Association’s research, advocacy, and tracking of machine learning (ML), deep learning, AI, and generative AI. Reporting to the ARL senior director for Scholarship, Policy, and Engagement Strategy and working closely with CNI leadership, Natalie plays a key role in the ongoing collaboration between CNI and ARL around AI/ML technologies and applications.
In addition to her role at ARL/CNI, Meyers is a research specialist at SDSC and recently served as professor of the practice at the Lucy Family Institute for Data & Society and prior to that as e-research librarian at the Navari Family Center for Digital Scholarship at the University of Notre Dame. She is co-chair of the Artificial Intelligence/Data Visitation Working Group of the Research Data Alliance (RDA) and co-author of the group’s AI Bill of Rights Recommendation. She has published and spoken extensively on various aspects of computational research and AI, including the recent “Ten Simple Rules for Good Model-Sharing Practices” in PLOS Computational Biology.
Norman Mooradian
Norman Mooradian has had a multifaceted career working as an information professional and as an academic focusing on digital ethics. He received his Ph.D. and M.A. in Philosophy from the Ohio State University. He also completed graduate courses in Legal Studies at the University of Illinois and attained the CIPP/US Information Privacy Professional Certification from the IAPP. Mooradian has published articles in areas such as information ethics, business ethics, information privacy, enterprise content management (ecm), knowledge management, and virtual reality, and he is the author of Ethics for Records and Information Management (2018, ALA). His research and teaching interests connect concepts from applied ethics, epistemology and ontology to the information sciences.
Alamir Novin
Novin is an Assistant Professor at the University of South Carolina, where he lectures on Artificial Intelligence, coding languages for Machine Learning, and data-driven management and AI policy. Prior to his current employment in research, Novin did data science and data journalism. He then joined one of the only research teams in Canada studying science media models (The Concordia Science Journalism Program) and researched Data Journalism alongside Data Science. As a Data Scientist, he built software online aimed at facilitating these newly discovered models and tested them on both scientists and science journalists. The experiments yielded positive results and I expanded my research into the area of Information Science and Human-Computer Interactions at the University of British Columbia. The focus of his current research uses Cognitive Science and Data Science to experiment with computer systems and Artificial Intelligence.
Vishnu Pendyala
Vishnu S. Pendyala, PhD is a faculty member in Applied Data Science and an Academic Senator with San Jose State University, current chair of the IEEE Computer Society Santa Clara Valley Chapter, and IEEE Computer Society Distinguished Contributor. During his recent 3-year term as an ACM Distinguished Speaker and before that as a researcher and industry expert, he gave numerous (70+) invited talks at conferences, faculty development programs, and other forums some of which are available on YouTube and IEEE.tv. He is a senior member of the IEEE and has over two decades of experience in the software industry in the Silicon Valley, USA. His book, “Veracity of Big Data,” is available in several libraries, including those of MIT, Stanford, CMU, the US Congress and internationally. Two other books on machine learning and software development that he edited are also well-received and found place in the US Library of Congress and other reputed libraries.
Xiaoying Song
Xiaoying Song is a Ph.D. student in University of North Texas, concentrating in data science. Her research area lies in computational social science, particularly in the realm of online misbehavior detection and countering. With proficiency in programming languages such as Python and R, she has undertaken extensive work in machine learning and data mining. Currently, she serves as a research assistant in UNT, leading a project of constrained large language model generations.